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Radar-rain gauge combined rainfall estimation method based on space-time local model

A space-time local, rain gauge technology, applied in the direction of rainfall/precipitation gauges, measuring devices, radio wave measurement systems, etc., can solve the problems of large local errors and low estimation accuracy, and achieve the effect of improving accuracy

Active Publication Date: 2020-06-19
海南省气象科学研究所
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Problems solved by technology

However, the existing spatio-temporal dynamic Z-R relationship method still has the problem that the estimation accuracy is not high or needs to be calibrated
Although rain gauge calibration can reduce the systematic error of regional radar quantitative precipitation estimation, there may still be large local errors

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Embodiment Construction

[0031] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0032] like figure 1 and 2Shown, the present invention a kind of radar-rain gauge joint precipitation estimation method based on spatiotemporal local model, described method comprises the following steps:

[0033] Step 1: Preliminary quality control of rain gauge observation data: according to the rain gauge △t 1 The lower limit of the minute rainfall is MINmm, and the upper limit is MAX mm, and preliminary quality control is carried out on the observation data of the rain gauge; among them, 1≤△t 1 ≤60;

[0034] Step 2: Radar echo quality control: through super-refractive surface object echo identification and removal, echo hole filling, radar beam blocking correction, and isolated noise echo removal processing, the quality control of radar echo is carried out;

[0035] Step 3: Radar volume scan data gridding: Invert the grid coordinates of L km×L k...

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Abstract

The invention discloses a radar-rain gauge combined rainfall estimation method based on a space-time local model. The method comprises the following steps: conducting preliminary quality control of observation data of a rain gauge; conducting radar echo quality control, gridding radar body scanning data, averaging radar echo time weight, constructing a radar echo-rain gauge sample pair, dividing radar echo, conducting quality control over sample pairs with observation values of a radar and the rain gauge through a space-time local model, establishing a precipitation echo grid point position Z-R relation through the space-time local model, realizing precipitation estimating and radar precipitation estimated value calibrating. The beneficial effects of the invention are that: the radar-raingauge combined rainfall estimation method based on a space-time local model divides rainfall echoes and non-rainfall echoes more scientifically, carries out the quality control of a Z-R sample pair more meticulously, carries out the more accurate modeling of a Z-R relation changing along with the space, and further improves the precision of radar-rain gauge combined rainfall estimation.

Description

technical field [0001] The invention relates to the field of objective analysis of precipitation in meteorology, in particular to a radar-rain gauge joint precipitation estimation method based on a spatio-temporal local model. Background technique [0002] When using radar to quantitatively estimate precipitation, if non-precipitation echoes are not identified and removed, precipitation will be overestimated. To this end, people have developed echo recognition algorithms based on fuzzy logic, threshold method, etc., to identify and eliminate non-precipitation echoes in radar echoes. However, the echo recognition algorithm based on fuzzy logic is not effective for particularly strong non-precipitation meteorological echoes, and it is still unable to distinguish between non-precipitation meteorological echoes and weak precipitation echoes. A radar echo of any intensity may correspond to a precipitation intensity other than 0, and a radar echo of any intensity with a reflectiv...

Claims

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Application Information

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IPC IPC(8): G01W1/14G01S13/86G01S13/95
CPCG01S13/86G01S13/95G01W1/14Y02A90/10
Inventor 张国峰田光辉蔡大鑫白蕤佟金鹤
Owner 海南省气象科学研究所
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